Deep Learning with Caffe
This course will teach you to build your very own convolutional neural network with Caffe to solve custom image classification problems.
What you'll learn
There are many deep learning frameworks to choose from. Caffe, which is written with speed, expression, and modularity in mind, is a great contender to be your framework of choice. In this course, Deep Learning with Caffe, you’ll learn to use Caffe to build a convolutional neural network that will help you classify a given set of images.
First, you’ll explore what deep learning is, how it differs from traditional machine learning, and how a neural network functions. Next, while building your very own convolutional neural network, you’ll learn how to prepare data for deep learning, define the model and solver, and train the model. Finally, you’ll discover how to improve the performance of your model using transfer learning.
When you’re finished with this course, you’ll have the skills and knowledge necessary to build your very own CNN using Caffe that’ll help solve custom image classification problems.
Table of contents
- Module Introduction 1m
- Basics of Computer Vision 2m
- What Are Convolutional Neural Networks? 1m
- CNN: Convolutions 4m
- CNN: Activation and Pooling 3m
- CNN: Classification 1m
- Demo: Introduction to the Dataset 3m
- What Is Caffe? 1m
- Demo: Data Preparation 5m
- Demo: Model Definition 5m
- Demo: Solver Definition 2m
- Demo: Training and Prediction Using the Model 2m
- Summary 1m
About the author
Pratheerth is a Data Scientist who has entered the field after an eclectic mix of educational and work experiences. He has a Bachelor's in Engineering in Mechatronics from India, Masters in Engineering Management from Australia and then a couple of years of work experience as a Production Engineer in the Middle East. Then when the A.I bug bit him, he dropped everything to dedicate his life to the field. He is currently working on mentoring, course creation and freelancing as a Data Scientist.